Respiratory illnesses such as asthma, chronic obstructive pulmonary disease (COPD), bronchitis, emphysema, and pneumonia affect many individuals. The ability to quickly detect and forecast the onset of these conditions, including possible life threatening events associated with these conditions, is of vital importance to those affected. Generally, diagnosis of these respiratory illnesses involves a doctor that listens to patient's breathing using a stethoscope. A stethoscope is an acoustic medical device for auscultation. It typically has a small disc-shaped resonator that is placed against the skin, and a tube connected to two earpieces. However, these traditional stethoscopes are prone to error and require a doctor to be present and to make the diagnosis. The need for a doctor makes daily monitoring for these conditions impractical.
A number of patents and applications have been filed that attempt to deal with these issues. U.S. Pat. No. 9,848,848 describes a digital stethoscope that uses a number of audio filters to control noise and reduce the possibility of error. U.S. Patent Pub. No. 2018/0317876 describes using a classification system, such as a binary support vector machine, to distinguish between those noises that are normal from those that are abnormal.
However, a number of limitations still exist in the art. For example, there is a need to improve real-time performance of the classification algorithm to allow it to be executed in real time and locally on a device that exists at the patient's home. There may be a need to improve the ability to forecast future respiratory future respiratory events. There may be a need to catalog data collected from in-home stethoscopes, while protecting a patient's privacy interest. Currently, a classification system may be able to predict whether a noise is normal or abnormal, but cannot predict a severity of a future respiratory event or the characteristics of that respiratory event. Methods, devices, and systems are needed to address these issues.